Interpreting Line Drawing Images: A Knowledge Level Perspective

Image understanding systems rely heavily on a priori knowledge of their application domain, often exploiting techniques developed in the wider field of knowledge-based systems (KBSs). Despite attempts, typified by the KADS/CommonKADS projects, to develop structured knowledge engineering approaches to KBS development, those working in image understanding continue to employ unstructured 1st generation KBS methods. We analyse some existing image understanding systems, concerned with the interpretation of images of line drawings, from a knowledge engineering perspective. Attention focuses on the relationship between the structure of the systems considered and the KADS/CommonKADS models of expertise, sometimes called generic task models. Mappings are identified between each system and an appropriate task model, identifying common inference structures and use of knowledge. This is the first step in the acquisition of models of the expertise underpinning drawing interpretation. Such models would bring significant benefits to the design, maintenance and understanding of line drawing interpretation systems.

[1]  Satoshi Suzuki,et al.  MARIS: map recognition input system , 1990, Pattern Recognit..

[2]  R. Gregory The intelligent eye , 1970 .

[3]  Ihsin T. Phillips,et al.  Empirical Performance Evaluation of Graphics Recognition Systems , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  David Marr,et al.  Representing Visual Information , 1977 .

[5]  S. Sutherland Seeing things , 1989, Nature.

[6]  D. S. W. Tansley,et al.  Knowledge-Based Systems Analysis and Design: A Kads Developer's Handbook , 1993 .

[7]  B. Chandrasekaran,et al.  Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design , 1986, IEEE Expert.

[8]  E. Land The retinex theory of color vision. , 1977, Scientific American.

[9]  Bob J. Wielinga,et al.  KADS: a modelling approach to knowledge engineering , 1992 .

[10]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[11]  Jan J. Gerbrands,et al.  Knowledge-Based Interpretation of Utility Maps , 1996, Comput. Vis. Image Underst..

[12]  Paul H. Lewis,et al.  A knowledge based line recognition system , 1990, Pattern Recognit. Lett..

[13]  Guus Schreiber,et al.  KADS : a principled approach to knowledge-based system development , 1993 .

[14]  H. Barrow,et al.  RECOVERING INTRINSIC SCENE CHARACTERISTICS FROM IMAGES , 1978 .

[15]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[16]  Richard Lepage,et al.  Knowledge-Based Image Understanding Systems: A Survey , 1997, Comput. Vis. Image Underst..

[17]  William J. Clancey,et al.  Heuristic Classification , 1986, Artif. Intell..

[18]  J. Beck Surface color perception , 1972 .

[19]  Tony P. Pridmore,et al.  Interpreting Aerial Images: A Knowledge-Level Analysis , 2002 .

[20]  David L. Waltz,et al.  Generating Semantic Descriptions From Drawings of Scenes With Shadows , 1972 .

[21]  Kenneth J. Turner,et al.  Computer perception of curved objects using a television camera , 1974 .

[22]  D. Marr,et al.  Analysis of occluding contour , 1977, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[23]  Philippe Corriveau Book review: Knowledge-Based Systems Analysis and Design-A KADS Developer's Handbook by Stewart W. Tansley and Clive C. Hayball (Prentice Hall 1993) , 1995 .

[24]  Indranil Chakravarty,et al.  A Generalized Line and Junction Labeling Scheme with Application to scene Analysis , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  L. M. MILNE-THOMSON,et al.  Vector and Tensor Analysis , 1949, Nature.

[26]  Gilbert Falk,et al.  Interpretation of Imperfect Line Data as a Three-Dimensional Scene , 1970, Artif. Intell..

[27]  Jon Sticklen,et al.  Knowledge-based segmentation of Landsat images , 1991, IEEE Trans. Geosci. Remote. Sens..

[28]  Berthold K. P. Horn Understanding Image Intensities , 1977, Artif. Intell..

[29]  Tony P. Pridmore,et al.  Knowledge-Directed Interpretation of Mechanical Engineering Drawings , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Guus Schreiber,et al.  Knowledge Engineering and Management: The CommonKADS Methodology , 1999 .

[31]  David A. Huffman,et al.  Curvature and Creases: A Primer on Paper , 1976, IEEE Transactions on Computers.

[32]  F. Almgren,et al.  The Geometry of Soap Films and Soap Bubbles , 1976 .

[33]  Thomas O. Binford,et al.  Inferring Surfaces from Images , 1981, Artif. Intell..

[34]  Lawrence G. Roberts,et al.  Machine Perception of Three-Dimensional Solids , 1963, Outstanding Dissertations in the Computer Sciences.

[35]  Kent A. Stevens Constraints on the Visual Interpretation of Surface Contours , 1979 .

[36]  Kent A. Stevens,et al.  Surface perception from local analysis of texture and contour , 1980 .